hey where can i learn about segmentation and how to use the fast.ai library for segmentation
Image segmentation is a vast field, being one of the most fundamental tasks in computer vision, so acquiring a firm grasp on all the state-of-the-art techniques overnight is infeasible. Instead, I suggest you begin with a relatively simple and traditional model, U-Net, and gradually work your way to more advanced alternatives. Jeremy Jordan has a blog post on segmentation and U-Net, also containing a further reading section you can refer to in order to look up other architectures.
As for segmentation using fastai, the first chapter of the book has a brief rundown on this topic and trains a U-Net on the CamVid dataset, which can serve as a gentle yet practical introduction to what you are seeking. Afterwards, you can go through relevant Kaggle notebooks such as this, this, and this that employ fastai (possibly in conjunction with other segmentation libraries, e.g.,
segmentation_models_pytorch) to conduct segmentation on various datasets.
Noted Thank you very much